This invention relates generally to telecommunications systems and more specifically, to methods and systems for dynamically forcing and distributing calls to agents within large team call servicing centers.
Force management systems for large team call servicing centers are well known in the prior art. These systems forecast the required number of call handling agents to handle the anticipated call volume as well as distribute calls to the call handling agents in some predetermined manner.
In determining the required number of agents to handle the anticipated call volume, call centers rely primarily on two variables: the estimated, or offered, load and grade of service. The offered load is a unit of measurement reflecting the estimated total work time of the incoming call traffic and is calculated by multiplying the estimated number of calls within a certain time period by the estimated average work time for those calls. In estimating the number of calls, current force management systems typically utilize time-series analyses of historic data as well as current telephone switch monitored data to forecast the number of incoming calls for a particular time period. Once the offered load is calculated, the number of agents required to service this specific load is determined. Typically, further adjustments are made to the number of agents working within a particular period of time as force managers evaluate the previous time period""s results as well as the trends for the day. In U.S. Pat. No. 5,185,780 to Leggett a method for predicting the required number of agents required to provide a given service level in a force management system is taught. Under this method, the force management system generates call handling performance data from which an offered load is calculated. Using this offered load value, the method calculates predictor values and uses these values in successive Erlang C calculations to locate the desired number of agents required to provide a given service level.
As the Leggett invention teaches, present call center force management systems attempt to match the appropriate number of agents with the estimated offered load to ensure that some predetermined acceptable level of service is achieved. There are many parameters by which the level, or grade, of service to the calling customer may be evaluated. However, the two most typical measurements include average delay in queue (xe2x80x9caverage delayxe2x80x9d) and percent abandon. Average delay refers to the length of time a caller must wait in queue before the caller is connected to an agent position. Percent abandon refers to the percentage of callers who abandon their efforts to seek agent assistance. Understandably, there is a very strong correlation between average delay and percent abandon.
Another aspect of the agent staffing function that critically affects the ability to manage service levels is the agent work force configuration. Current state of the art utilizes a single, large team approach that allows any incoming call to reach any call agent Under this approach, the offered load must be calculated for each distinct period of time and management must schedule a corresponding single, large team of agents to meet this offered load while providing a predetermined service level. An example of the range of agent team size necessary to try to meet the offered load demonstrates the wide variability in team size throughout a twenty-four hour period. In one specific type of large team call center, telephone directory assistance, team sizes may range from as few as 30 call agents in the early morning hours to as many as 250 agents and more during the peak busy hours.
Under the single, large team methodology, management may need to make adjustments to the large agent team when service reaches some critical level by scheduling one or more additional agents. For example, when the offered load exceeds the carried load for a particular increment of time, e.g. 15 minutes, 30 minutes, etc., the result is a degradation in service. When service is degraded, the average delay and the percent abandons both increase in some concomitant manner. This percent abandon value may be as high as 20-50% for some quarter hour intervals. Typically, management this agent workforce adjustment by monitoring and evaluating the results of a particular time period for a service degradation, deciding how best to manage the service degradation, and finally arranging for additional agent resources, if needed, by calling in additional agents or offering overtime to those agents presently on duty. It is important to note that no existing force management system is capable of making dynamic adjustments to agent team size in real-time.
In addition to estimating the required number of agents, current force management systems distribute calls to the agents in some predetermined manner. Typically, calls are distributed by an automatic call distributor (ACD) to one of a plurality of call agents based on some predetermined notion of xe2x80x9cfairness.xe2x80x9d For example, in U.S. Pat. No. 5,828,747 to Fisher, et al. a call distribution methodology is taught based on an individual agent""s occupancy. Call occupancy refers to the amount of time that an agent spends on actually handling calls and is typically expressed as a percentage of the total amount of time the agent has been available to handle a call. Under the Fisher methodology, individual agent occupancies are calculated and a queue of available agents is ordered in the inverse order of the agents occupancies. Calls are distributed to the agents in the inverse order of their individual agent occupancies specifically to improve the equity of the call distribution.
Other call distribution methodologies based on some notion of xe2x80x9cfairnessxe2x80x9d include the distribution of calls to an agent who has been idle the longest or the distribution of calls to an agent to ensure that all agents handle an equal number of calls. Idle time re-refers to that period of time in which the agent is not handling a call or performing a call related task. Lastly, other call distribution methodologies include distributing calls based on a caller""s originating number or geographic location.
Current force management systems may also attempt to perform the agent forcing and call distribution function in some cost-optimizing manner. Call centers often attempt to strike a balance between satisfying the grade of service objectives and minimizing the agent variable costs. When the offered load exceeds the carried load, the call volume that is actually being handled by the call agents, service is degraded and customers abandon their efforts to seek assistance from an agent. The percent abandon increases and service may be significantly degraded. Moreover, this increase in the number of callers who abandon their calling efforts results in a portion of these same callers attempting to seek agent assistance again. These regenerated attempts are not random and cause the offered load to further increase exponentially, thereby exacerbating the percent abandon service problem. Conversely, when the offered load is less than the carried load, agents are idle, resulting in an inefficient use of labor. Neither of these conditions results in optimal performance. An increasing percentage of abandoned calls indicates customer dissatisfaction with the company; correspondingly, reducing the percentage of abandoned calls by increasing the number of available agents may drive up cost beyond an optimal level.
In addition to minimizing agent cost, current methodologies may attempt to optimize agent utility either by distributing calls to an agent with a particular skill or by utilizing an agent""s idle time to perform tasks other than the handling of calls. U.S. Pat. No. 5,206,903 to Kohler et al. teaches an automatic call distribution in which each incoming call, with each call having been assigned up to three prioritized skill numbers, attempts to be matched with an agent possessing that particular skill. Each agent possesses up to tour skill numbers representing various particular abilities of the agent and agents are arranged in static groups relating to the particular skills each agent possesses. Upon the arrival of the incoming call, a search is made for a match between the caller skill number and an available agent possessing that skill. This search is conducted sequentially, with a search being conducted on the first skill number before a search is conducted on the either the second or third skill number. Finally, if no match is found with any one of the skill numbers, the search of available agents is expanded to other groups of agents.
There are a number of other reasons why average delay may exceed the stated service objective in addition to a particular call distribution methodology. Among the most important are the following. First, the calls that arrive are not random. A call center may experience call volume xe2x80x9cpeaksxe2x80x9d at certain non-random times. For example, calls often arrive a few minutes or seconds after the hour or half hour due to television commercial breaks. If calls are delayed because of a two or three minute problem, the force data management systems currently used would be unable to detect it. These current systems look only at a thirty second delay during a fifteen minute period and determine from that if additional operators are needed.
A second factor may be agent practice. An agent often may leave a position a few minutes early or occupy a position a few minutes late. Additionally, an agent may place the position in a xe2x80x9cmake-busyxe2x80x9d state or take a short relief, temporarily making the agent unavailable to handle calls. Although the calls arrive as forecasted, these agent practices effectively reduce the number of available agents for short periods of time. In addition to specific agent work practices, an agent""s ability to handle calls within an estimated average work time (AWT) may significantly impact the average delay. A new or inexperienced agent as well as the introduction of a new operating practice to experienced agents may cause an agent to handle calls more slowly than anticipated. For example, some operators may have an AWT of five minutes for a few calls in contrast to the normal AWT of thirty seconds. This increased AWT means that an agent is not able to handle as many calls as estimated. In addition, when operators release a lower percentage of their calls to the audio response unit (ARU) than desired, AWT will increase, thus causing a rise in average delay.
Another factor that can contribute to average delay exceeding the objective is actual offered load. It should be appreciated that when offered load exceeds the estimated load, either because AWTs are higher or lower than expected or because the volume of incoming calls is higher than expected, this will contribute to a higher average delay. Additionally, when all positions are occupied, a position shortage can occur which can drive up the average delay. Further, equipment problems, such as out of service positions or excessive/slow log in time, and network problems, such as regenerated attempts, can also cause the average delay to be increased.
In contrast to a call distribution methodology based on a single, large team, call routing utilizes fundamental network engineering principles to route calls over a complex, tiered telecommunications network. Call routing refers to sending a call from the originating location to the final destination over a telecommunications network composed of telephone switches and telephone trunk lines. The fundamental network engineering principle used to design this complex network is that a number of smaller direct trunk groups between two points is far less efficient than fewer, larger, more efficient trunk groups with an overflow response capability. By concentrating the originating call volume into larger, more efficient trunk groups these trunk groups are able to operate at a much higher percent occupancy.
This increase in network efficiency is achieved by creating a hierarchical, or tiered, trunking arrangement. Under this arrangement, all calls are first offered to one or more high usage (xe2x80x9cHUxe2x80x9d) trunk groups. These HU trunks receive random traffic or calls and are engineered to operate at near 100% occupancy. This maximum occupancy is accomplished by offering much more traffic to the HU trunks than the HU trunks can carry. The call traffic that the HU trunks are not able to carry overflows to a second level of trunks, the alternate route (xe2x80x9cARxe2x80x9d) trunk groups.
AR trunk groups handle traffic that is not random. Rather, the AR trunks receive calls that have overflowed from multiple HU trunk groups. Alternate trunk groups also run at high occupancy levels, often at the 90 percent and greater levels during peak periods. As with the HU trunks, these AR trunk groups are also designed to overflow to final trunk groups. These final trunk groups are designed to receive peak load calls and are engineered to operate at a pre-determined service level. The result of this complex network is that large, highly efficient HU and AR trunk groups complete most of the calls with final trunk groups completing the remaining calls. As an example of the gains in efficiency obtained under this network methodology, a single large combined trunk group might require 300 individual trunks, but by dividing trunks into tiered trunk groups, i.e. high usage trunk groups, alternate trunk groups, and final trunk groups, the total number of trunk circuits is reduced to 250 or less, an almost 17%, reduction.
One object of the present invention is to provide a method and apparatus for dynamically matching carried load with the incoming call traffic offered load.
Another object of the present invention is to provide a method and apparatus for dynamically determining an enhanced, hierarchical, agent work force team configuration at any given point in time, utilizing the optimization techniques of the present invention.
Another object of the present invention is to provide a method and apparatus for distributing calls to a plurality of agents in a manner that improves agent variable costs.
Another object of the present invention is to provide a method and apparatus for dynamically determining a threshold delay between various pairs of agent teams to provide a predetermined grade of service at any given point in time.
Another object of the present invention is to provide a method and apparatus for improving the management and quality of service provided to customers seeking agent assistance.
Yet another object of the present invention is to provide a method and apparatus for improving agent call occupancy utilizing novel optimization techniques.
Still another object of the present invention is to provide a method and apparatus for minimizing the cost of an agent work force by utilizing idle time in a last or final team productively for training or education.
In accordance with the stated objectives, in one aspect of the present invention, a method of distributing calls to a plurality of agents comprises the step of assigning each of the plurality of agents to one of a plurality of teams. The plurality of teams are configured into a hierarchy that includes at least a primary team and a final team. At least a portion of the incoming calls are initially distributed to the primary team. A call is redistributed according to the hierarchy from the primary team toward the final team if the call is not answered by an agent of the primary team within a predetermined period of time.
In another aspect of the present invention, a call management system comprises a means for configuring a plurality of agents into a plurality of teams with a hierarchical structure. Also included are a means for delaying a majority of incoming calls a predetermined period of time and a means for monitoring call handling data, force management variables and performance data. A means for adjusting in real time at least one of team configuration and the predetermined period of time is also included.
In yet another aspect of the present invention, an article comprises a computer-readable data storage medium. A means is recorded on the medium for determining a call delay time period and a configuration of agents into a hierarchy of teams as a function of the call data, the force management variables and the performance data.